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Simulation stands as a cornerstone for safe and efficient autonomous driving development.
Pointnet: Deep learning on point sets for 3d classification and segmentation
C. R. Qi, H. Su, K. Mo, and L. J. Guibas · 2016
Earlier work this paper cites.
Waymo open dataset: An autonomous driving dataset, 2019
Waymo LLC · 2019
Earlier work this paper cites.
Trafficsim: Learning to simulate realistic multi-agent behaviors
S. Suo, S. Regalado, S. Casas, and R. Urtasun · 2021
Earlier work this paper cites.
Scenegen: Learning to generate realistic traffic scenes
S. Tan, K. Wong, S. Wang, S. Manivasagam, M. Ren, and R. Urtasun · 2021
Earlier work this paper cites.
Large scale interactive motion forecasting for autonomous driving: The waymo open motion dataset
S. Ettinger, S. Cheng, B. Caine, C. Liu, H. Zhao, S. Pradhan, Y. Chai, B. Sapp, C. R. Qi, Y. Zhou, et al · 2021
Earlier work this paper cites.
LoRA: Low-rank adaptation of large language models
E. J. Hu, Y. Shen, P. Wallis, Z. Allen-Zhu, Y. Li, S. Wang, L. Wang, and W. Chen · 2022
Earlier work this paper cites.
The waymo open sim agents challenge
N. Montali, J. Lambert, P. Mougin, A. Kuefler, N. Rhinehart, M. Li, C. Gulino, T. Emrich, Z. Yang, S. Whiteson, B. A. White, and D. Anguelov · 2023
Earlier work this paper cites.
BITS: Bi-level imitation for traffic simulation
D. Xu, Y. Chen, B. Ivanovic, and M. Pavone · 2023
Cited alongside, same era.
Guided conditional diffusion for controllable traffic simulation
Z. Zhong, D. Rempe, D. Xu, Y. Chen, S. Veer, T. Che, B. Ray, and M. Pavone · 2023
Cited alongside, same era.
Motiondiffuser: Controllable multi-agent motion prediction using diffusion, 2023
C. M. Jiang, A. Cornman, C. Park, B. Sapp, Y. Zhou, and D. Anguelov · 2023
Cited alongside, same era.
Language-guided traffic simulation via scene-level diffusion
Z. Zhong, D. Rempe, Y. Chen, B. Ivanovic, Y. Cao, D. Xu, M. Pavone, and B. Ray · 2023
Cited alongside, same era.
Trafficgen: Learning to generate diverse and realistic traffic scenarios
L. Feng, Q. Li, Z. Peng, S. Tan, and B. Zhou · 2023
Cited alongside, same era.
Llama: Open and efficient foundation language models, 2023
H. Touvron, T. Lavril, G. Izacard, X. Martinet, M.-A. Lachaux, T. Lacroix, B. Rozière, N. Goyal, E. Hambro, F. Azhar, A. Rodriguez, A. Joulin, E. Grave, and G. Lample · 2023
Later among the works it cites.
The 2nd place solution for 2023 waymo open sim agents challenge, 2023
C. Qian, D. Xiu, and M. Tian · 2023
Later among the works it cites.
Trajeglish: Traffic modeling as next-token prediction
J. Philion, X. B. Peng, and S. Fidler · 2024
Closest in time.
Smart: Scalable multi-agent real-time simulation via next-token prediction, 2024
W. Wu, X. Feng, Z. Gao, and Y. Kan · 2024
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Mtr++: Multi-agent motion prediction with symmetric scene modeling and guided intention querying
S. Shi, L. Jiang, D. Dai, and B. Schiele · 2024
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Versatile scene-consistent traffic scenario generation as optimization with diffusion, 2024
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S. Tan, B. Ivanovic, X. Weng, M. Pavone, and P. Kraehenbuehl · 2023
Cited alongside, same era.
Realgen: Retrieval augmented generation for controllable traffic scenarios
W. Ding, Y. Cao, D. Zhao, C. Xiao, and M. Pavone · 2023
Cited alongside, same era.
TrafficBots: Towards world models for autonomous driving simulation and motion prediction
Z. Zhang, A. Liniger, D. Dai, F. Yu, and L. Van Gool
Cited in the paper.
Learning realistic traffic agents in closed-loop
C. Zhang, J. Tu, L. Zhang, K. Wong, S. Suo, and R. Urtasun
Cited in the paper.
Z. Huang, Z. Zhang, A. Vaidya, Y. Chen, C. Lv, and J. F. Fisac · 2024
Closest in time.